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We meet a lot of R users on our travels, and something we often hear from them is that while they're doing amazing things with R (incredible data visualizations, statistical analysis, and data science applications), their supervisors or peers may not know that the R language is involved, or that others could benefit from using it. It would be great, they tell us, to have something short and sweet to share that describes what makes R so special. 

by Andrie de Vries

Prior to joining Revolution Analytics in March this year, I spent several years in the field of market research and survey analytics. During this period, I spent a few months consulting to a digital marketing agency based in London. My role was to help build their capability in building customer surveys and integrating these into social media sites, including Facebook and Twitter.

Many cities around the world have bike sharing programs: pick up a bike at a docking station, ride it across town and drop it off at another session, and just pay for the time you use.

I just got back from a three-week trip overseas, and one of my favourite things about coming home after being away is the super-enthusiastic welcome I get from our Jack Russels, Max and Easy. It reminded me of the clip below.

O'Reilly Media has published a new whitepaper, Real-Time Big Data Analytics: Emerging Architecture. This 32-page document describes the processes and components necessary for getting on-demand information from big-data stores such as Hadoop.

Thomas Levine has put together a handy list of "data spells" for R: all of those cool, slightly hacky ways of getting things done with R that you might not come across in the standard documentation. Check out the link below for handy hints on importing data, handling lists and factor objects, using .Rprofile to configure your standard R environment, and much more. R spells for data wizards

I'm a bit late catching up on this, but Mario Inchosa (Revolution Analytics US Chief Scientist) gave a standing-room-only talk on high-performance predictive analytics in R and Hadoop at last month's Hadoop Summit.

The most recent edition of the Revolution Newsletter came out a couple of weeks ago. In case you missed it, the news section is below, and you can read the full July edition (with highlights from this blog and community events) online.